CASCB talk: Studying emotions at individual and collective levels with social media data
Time
Monday, 3. July 2023
15:30 - 16:45
Location
ZT 702 and online
Organizer
CASCB
Speaker:
Prof. Dr. David Garcia, University of Konstanz
This event is part of an event series „Seminar Series Summer Semester 2023“.
Studying emotions at individual and collective levels with social media data
The wealth of data generated by our digital society, when analyzed through computational methods like natural language understanding, provides a new window to study human behaviour at new scales and resolutions. This enables the analysis of social phenomena in which temporal dynamics and network structures require the use of large and detailed data. I will present an overview of my work on the analysis of emotions with social media data, one of the most accessible and powerful data sources in our digital society. A validation study against representative survey data shows the potential of social media macroscopes of emotions to track the emotions of a society, a method that we applied to study collective emotions and their relationship to solidarity after a terrorist attack. This has motivated our further work on emotion detection on social media data at the individual level and further applications of natural language processing to study online affective life.
David Garcia is Professor for Social and Behavioural Data Science at the University of Konstanz since October 2022. He also holds appointments at the Graz University of Technology and the Complexity Science Hub Vienna, where part of his research lab is co-located. David holds computer science degrees from Universidad Autonoma de Madrid (Spain) and ETH Zurich (Switzerland). David did a PhD and Postdoc at ETH Zurich, working at the chair of systems design. His research focuses on computational social science, designing models and analysing human behaviour through digital traces. His main work revolves around the topics of emotions, polarization, inequality, and privacy, combining statistical analyses of large datasets of online interaction with computational models. David’s work lies at the intersection of various scientific disciplines, combining methods from network science, computer science, and statistical physics to answer questions from psychology and political science.
